{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>发票编号</th>\n",
       "      <th>分店</th>\n",
       "      <th>城市</th>\n",
       "      <th>顾客类型</th>\n",
       "      <th>性别</th>\n",
       "      <th>商品类别</th>\n",
       "      <th>商品单价（美元）</th>\n",
       "      <th>购买数量（件）</th>\n",
       "      <th>购买日期</th>\n",
       "      <th>时间</th>\n",
       "      <th>支付方式</th>\n",
       "      <th>支付费用（美元）</th>\n",
       "      <th>收益（美元）</th>\n",
       "      <th>购物体验评分</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>426-39-2418</td>\n",
       "      <td>分店C</td>\n",
       "      <td>城市C</td>\n",
       "      <td>普通顾客</td>\n",
       "      <td>男</td>\n",
       "      <td>电子配件</td>\n",
       "      <td>61.41</td>\n",
       "      <td>7</td>\n",
       "      <td>2020-01-14</td>\n",
       "      <td>10:02:00</td>\n",
       "      <td>现金</td>\n",
       "      <td>429.87</td>\n",
       "      <td>21.4935</td>\n",
       "      <td>9.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>527-09-6272</td>\n",
       "      <td>分店A</td>\n",
       "      <td>城市A</td>\n",
       "      <td>会员</td>\n",
       "      <td>女</td>\n",
       "      <td>电子配件</td>\n",
       "      <td>28.45</td>\n",
       "      <td>5</td>\n",
       "      <td>2020-03-21</td>\n",
       "      <td>10:17:00</td>\n",
       "      <td>信用卡</td>\n",
       "      <td>142.25</td>\n",
       "      <td>7.1125</td>\n",
       "      <td>9.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>761-49-0439</td>\n",
       "      <td>分店B</td>\n",
       "      <td>城市B</td>\n",
       "      <td>会员</td>\n",
       "      <td>女</td>\n",
       "      <td>电子配件</td>\n",
       "      <td>12.10</td>\n",
       "      <td>8</td>\n",
       "      <td>2020-01-19</td>\n",
       "      <td>10:17:00</td>\n",
       "      <td>电子钱包</td>\n",
       "      <td>96.80</td>\n",
       "      <td>4.8400</td>\n",
       "      <td>8.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>421-95-9805</td>\n",
       "      <td>分店A</td>\n",
       "      <td>城市A</td>\n",
       "      <td>普通顾客</td>\n",
       "      <td>女</td>\n",
       "      <td>电子配件</td>\n",
       "      <td>28.96</td>\n",
       "      <td>1</td>\n",
       "      <td>2020-02-07</td>\n",
       "      <td>10:18:00</td>\n",
       "      <td>信用卡</td>\n",
       "      <td>28.96</td>\n",
       "      <td>1.4480</td>\n",
       "      <td>6.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>811-03-8790</td>\n",
       "      <td>分店A</td>\n",
       "      <td>城市A</td>\n",
       "      <td>普通顾客</td>\n",
       "      <td>女</td>\n",
       "      <td>电子配件</td>\n",
       "      <td>45.48</td>\n",
       "      <td>10</td>\n",
       "      <td>2020-03-01</td>\n",
       "      <td>10:22:00</td>\n",
       "      <td>信用卡</td>\n",
       "      <td>454.80</td>\n",
       "      <td>22.7400</td>\n",
       "      <td>4.8</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          发票编号   分店   城市  顾客类型 性别  商品类别  商品单价（美元）  购买数量（件）       购买日期  \\\n",
       "0  426-39-2418  分店C  城市C  普通顾客  男  电子配件     61.41        7 2020-01-14   \n",
       "1  527-09-6272  分店A  城市A    会员  女  电子配件     28.45        5 2020-03-21   \n",
       "2  761-49-0439  分店B  城市B    会员  女  电子配件     12.10        8 2020-01-19   \n",
       "3  421-95-9805  分店A  城市A  普通顾客  女  电子配件     28.96        1 2020-02-07   \n",
       "4  811-03-8790  分店A  城市A  普通顾客  女  电子配件     45.48       10 2020-03-01   \n",
       "\n",
       "         时间  支付方式  支付费用（美元）   收益（美元）  购物体验评分  \n",
       "0  10:02:00    现金    429.87  21.4935     9.8  \n",
       "1  10:17:00   信用卡    142.25   7.1125     9.1  \n",
       "2  10:17:00  电子钱包     96.80   4.8400     8.6  \n",
       "3  10:18:00   信用卡     28.96   1.4480     6.2  \n",
       "4  10:22:00   信用卡    454.80  22.7400     4.8  "
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "data_supermarket = pd.read_excel(r'./dataset/超市销售数据.xlsx')\n",
    "data_supermarket"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 案例1：通过箱线图查看超市顾客支付费用的分布情况"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAApYAAAFACAYAAAAGfTylAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDIuMi4zLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvIxREBQAAG49JREFUeJzt3XucXWV97/HPL5PLxBBIQgiK5AKKGgmSmpx6ASVYquCljSV6uINJpaBAPBy5nVAu1h44AmpFUWkJUNqMiBcKCHLpCUJEhYRai6hQW7CHGm5JAIcCIfmdP9aasNmZyUzIk+y5fN6v137NWms/a61n7SeT+b6eZz1rR2YiSZIkbalhra6AJEmSBgeDpSRJkoowWEqSJKkIg6UkSZKKMFhKkiSpCIOlJEmSijBYSlILRcTwFp13ekTs1cN774yI9m1dJ0kDn8FSkl6hiDggIiZu4WFOiIjl9fFeExEZEaMKVK83XwGuiYjt6nOPiIjhETEdWAZ8dFM7R8RnI+LApm3HRMTlETEyIkZstZpL6rcMlpJUi4hvRcQFfSwbwN8A5/bw/jcj4oYe3nssIp6JiDXA/wZm1su/rIs8GhFrGl6jm/Y/sw6gfXld08355wHvBqYAayKiE3gW+ABwKhDAZyLiofq1MiImN+w/BTgdGNt06B2B92XmC8DSiPh0N+c+azPq3vX6ZHefo6T+x2ApaciJiJ0j4k0RsXtETOt6AW1Ae+O2iNitLrtz02HmAOOAs3o4zbPAkz28NxUYX78+ASzLzHHA3gCZOa5enwvsADzftP8LwA8yM7pewD8Af9W07cq6bOO1v5kqEJ8FHAP8Z2aOycwRwFPA4cBs4H8AI4BZwFuB/2w4zCLgG5l5TdNQ/irgmXr5NOBD3Qypr+2m7ucCn27c1vDePzdfg6T+qyX39khSix1HFY6eB9Y1bH8VsB44smHbMGAUVc9iY+/kmcBi4IWIeHV9rMbvyB0JEBHjqALaE/nSd+ieRxUaAbYDtouIh6j/T66XAdobfj7bcOzGOvfmxa6FOlQuA/4VuAB4HTA5Il4HPAFcBSzJzBUR8WvgNcBumbm84RhvBT4M7BURbwFuiogPZea99fW3RcTYuo7XAt+OiEWZ+dPm+tTH2w/4c2BYRFzY8NZ+mXlHd/tI6r8MlpKGnMw8l26GsCPiCuChzDxnU/tHxHuA9wB3An9GFdJ6cmj9czywpl5+PdCRmWdExHnA9MycW/ea/ntmTuvlEtYD+9bD513GAOsj4piGba8CljSs/wq4ArgQ2A94C1WoexJ4GvgMcCNAZq6JiKOB+xquezLwTapQ3Vnv+3Ngp4g4g2oofXfg/wE/q1+38vKe27UNx5sBfAf4MdXn+QJwM/BIQ6iElwd2Sf2YwVKSNkN9v+OlvDTk+yWqiTDPNfRIdoVUMvOYiBiVmY3D2ZOBAyLieGB0VTzWUN+e1BQYAR7PzD0a1pNq+HxOw/mupQrFn2quw4adMtcBJ9fvHQV8IDPfVa9/Avg8sKi6fXSDKyPi/Zn5faqh+tcBXwY+R3XrwJuphvMnAHdRDaOPa/ospjZdD/WkoRuoAv4HgOuAh6iG/uc2l5c0MBgsJQ1JEbED8DjwHFUPINRD4RHRFc4SeEdm/rLeJ4DLgN9Q9+TVE1WIiAMj4u7MXNV8rqZQSWbuXe/zJeB44C2Z+YuGHstxDfX8CPB/mqv/Ci+bhokws4GdI+JE4DHgv4AfN4bVuvwaqs8Iqt7M2cBPgWuo7pX8D+CMuuwM4BTg/RHxRmAm1b2okyJiTB1suz6D30XE2zLz0Yh4ELieKqh+rOF8kgYYJ+9IGpIy86nMHAksoLq/cGJmjszM9jrY/S1wd1eorG1PNdQ7v/FYETEM+DrVhJde1ZOGbgBOBM7MzF/0UO6dVPeDrmx6a0s6BZ6gCtTvphp6fgxYTRWi922ajb6GqgcRgMxcn5krgD+m6nX9cl3P4yNiKXB7XfQvgT2An1DdCjCxMVTW+0wBDo2I26k+65OAj1Pdf/pvEXFpff2SBhCDpaSh7ttUvXUbHmkTEW+gCpynNxbMzKeAfTLzoabt64EvUD2TckxPJ4qInSLiRuABYH+q+w3PaAhxPwWeqtdfqI/5W6pw2agd2K/xkTxUYW9h07ajm+uQmVcD/w7sRBUmF1ANQUM9O73xRTVTvPEa/oTqPs0vUgXRD1JNBvoiVQ/lj4AvZObxwG71Z9jdczmHA0dRDYHvR3Xf5puB91MNj+9BFXolDSAOhUsa0jJzfT08fEPd6/YA1ezoSzLzn7op39OM7KuoAtEs4I7uCmTm4xFxPfAXwPuAN2XmIQARcSgwOjMX1+tX1Psc082hJgDfzsx5XRv6co9lg/Op7odcC/wQWAr8FRtPCIKGHsvaX1JNFDqfapLOPZl5UsM57wLeGxE7UvVCnkT1GKLmz+LfqB5jRES0Ud0ScBpwCDA1My+v3+vhEiT1RwZLSUNeZt4REZ+jmpH8INXEnP+1mcd4MiKm1L2amyr3VYCIeH/XtvpZkJ+lCqSLG4qP7OEw06mGmTdbRCyk6km8BPgg1Uzwn1EFyJdNCKrLNwfNg4CVmflcQ5n2hvVvUYXVg4GPZua1vdTnjcA/Us0O/zTwm8xcu6l9JPVfDoVLGvLqeyQfpnok0L5UD+Xe7K9V7C1UNvk1cE9UX9/4FWAX4C8i4vsRcR1Vb+BXu6nr6LqOSze3fvUzKC+imhm+rq5zZuZ32fSEoKj3347q2ZYfjohzIuK6iHiUasINdS/lWXX5+6iGuYmIP4iXuh6bz/NIXZ+pVMH65mj6pqFe6iapHzFYShpyojIpIg6qeyofAk4ADgT+G9Vw9sqI+EZEnBQR74uIWU2HGcamA08b3Tx/MSJeGxEHUM18nkQVMOcBH6mHh0+mCrmfAr4REWc33bd5BNUzJ+/s5nxdD2XfLqqHl7+ehnsk64eYf7zuRRzJy3tE2+h58k5bXWYkcBPVczt3Aa4G3glcHhF/Btxfl/094LXAJXWYvQX4o/oYI4DhETEuqofHD6/fP5rqcUYXAaMa3m/D0TVpwPCXVdJQtJBqYsxKql61QzLzrob359SB6DDgT4E3Uc36XtFQZhgvBa4NIuJ9wF7AAcDl3Zx7N6qHhq8BllOFtCszcw1AZt4PnBgR51LdcziLanIRUX094tnApd3c6/kiL31DzXDgXqoZ4C/7vu6uexfZOFi20/NQeHu976qI2Kt+xFDX+yOp7td8A9UD07+UmVl/DjdTPUD+Z8D3Guq2D9VM9J5c1rTu3yppgIiGZ9hK0pBQD8u+PjMf7GP54cDwpvsKrwV+lplnNZU9iios3gackJkbBaiIGNcVJF9B3d9I9cD0jSbENJXbve4B7en9cVSThX77SurRTZ1WZebjTdsnAh8FvpOZK+ttZwHvaQ6wmzj2T4HLMvPiLa2npK3PYClJ2mbqQNveFTQlDS4GS0mSJBXh5B1JkiQV4Q3RLTJx4sScNm1aq6shSZLUqxUrVjyRmTv1Vs5g2SLTpk1j+fLlra6GJElSryLi4b6UcyhckiRJRRgsJUmSVITBUpIkSUUYLCVJklSEwVKSJElFGCwlSZJUhMFSkiRJRRgsJUmSVITBUpIkSUUYLCVJklSEwVKSJElFGCwlSZJUhMFSkiRJRRgsJUmSVITBUpIkSUUYLCVJklSEwVKSJElFGCwlSZJUhMFSkiRJRRgsJUmSVITBUpIkSUUYLCVJklSEwVKSJElFGCwlSZJUhMFSkiRJRRgsJUmSVITBUpIkSUUYLCVJklSEwVKSJElFGCwlSZJUhMFSkiRJRRgsJUmSVITBUpIkSUUYLCVJklSEwVKSJElFGCwlSZJUhMFSkiRJRRgsJUmSVITBUpIkSUUYLCVJklSEwVKSJElFGCwlSZJUhMFSkiRJRRgsJUmSVITBUpIkSUUYLCVJklSEwVKSJElFGCwlSZJUhMFSkiRJRRgsJUmSVITBUpIkSUUYLCVJklSEwVKSJElFGCwlSZJUhMFSkiRJRRgsJUmSVITBUpIkSUUYLCVJklSEwVKSJElFGCwlSZJUhMFSkiRJRRgsJUmSVITBUpIkSUUYLCVJklSEwVKSJElFGCwlSZJUhMFSkiRJRRgsJUmSVITBUpIkSUUYLCVJklSEwVKSJElFGCwlSZJUhMFSkiRJRRgsJUmSVITBUpIkSUUYLCVJklSEwVKSJElFGCwlSZJUhMFSkiRJRRgsJUmSVITBUpIkSUUYLCVJklSEwVKSJElFGCwlSZJUhMFSkiRJRRgsJUmSVITBUpIkSUUYLCVJklSEwVKSJElFGCwlSZJUhMFSkiRJRRgsJUmSVITBUpIkSUUYLCVJklSEwVKSJElFGCwlSZJUhMFSkiRJRRgsJUmSVITBUpIkSUUYLCVJklSEwVKSJElFGCwlSZJUhMFSkiRJRRgsJUmSVITBUpIkSUUYLCVJklSEwVKSJElFGCwlSZJUhMFSkiRJRRgsJUmSVITBUpIkSUUYLCVJklSEwVKSJElFGCwlSZJUxPBWV0B6pSZMmMDq1atbXY2WybO3J859utXVUB+MHz+eVatWtboakrTVGSw1YK1evZrMbHU1WuecHYb29Q8gEdHqKkjSNuFQuCRJkoowWEqSJKkIg6UkSZKKMFhKkiSpCIOlJEmSijBYSpIkqQiDpSRJkoowWEqSJKkIg+Ug54OZJUnqO/9ubhmDpSRJkoowWEqSJKkIg6UkSZKKMFhKkiSpCIOlJEmSiigaLCNiUkTs0MeyLQm1ETGhYXlKK+ogSZI0GG12uIuIIyLiT3t4+3jgkKbyv2paPy8ibgcejIh/iYj7I+LnEXF7RPx1Q7n59Xu3RcQv6jK3RcSKiPhiH+o5NSIuato2GvhuRIyJiHbgqojYvqnMayLijvpcja876v0br2OP3uohSZIE0NHRweTJk4kIIoLJkyfT0dGxUZkdd9xxQ5mIYMcdd6Sjo4OOjg5mzJjBsGHDaG9vJyJob29n2LBhzJgxY6NjtcLwvhSKiLuA/wISmAS0RURXgBwNzAMeAw4C5jTtvrpp/RLgGuAI4H5gF+BZ4Dbg0oZyLwKfz8y/iYjjgOcy84qImAN8oJf6vgr4PPDxhm0XAW+juualdb3XAddHxIrMPBkgM38LvHtTx6+dDyyOiI9l5tN9KC9Jkoaojo4OFi5cSFtbG7fccgsARx99NAsXLgTg0EMPpaOjg+OOO45nnnmG8ePHc+qpp3LBBRewevVq5s+fz9ixYzn22GPp7Oxkn3324eqrr2bevHncddddzJ07l0WLFm04VqtEZm7eDhHzgO0y84qm7YcBJwF/B3yEKoQCvBW4F/hyZn4rIs4DxgKvAx6kCqrPA/8CPJaZf1sf70jgTOC3VOFzPbASGAd8PzNP30QdTwF+mJl3NWxrB/alCqz7AjsA3wPagHu6wmFERPbwoTS/FxF7A3Mz89xNfWbdmT17di5fvnxzd9tsEcHmtvFAMZivrU/O2QHOearVtVAfDPl/q9IAsrV+X2fMmEFnZyeLFy9m//33B2Dp0qXMnz+fMWPGcN999zFjxgweeOABJkyYQEdHB/vvvz9Lly7lsMMOY+XKlUybNo0xY8Zw8cUXc+KJJzJ//nwWL168Yb3r53333Ve8/nUn3Oxey/Xlw4uIScC1wAvATlRhbCVwc2aeFxHjgO8DzwF/AIzIzOfqfX+cmW+PiLbMXBcRXwdmAa+mCo1jqXoOHwcC+Gxm3hoRRwDtPfRYHthLsLwqM49s2jYaeFd9DY3BciTwk8x8quuDA9YCu9XXuB1VqH0SeCQzD+7tXJuo17HAsQBTpkyZ9fDDD/dlty0y2L9BYEj/sTZYDhiD/fdQGmy2xt+WtrY2MpPnn3+eESNGALB27Vra29sBWLduHW1tbaxfv56I2FCuq0zX9ojgueeeo729nWeeeYaxY8duWO/6uW7duuL172uw7NNQeGY+FhH7A9cBe2fmixFxIbCsLvIuYBFwRh0ez42I5Zl5bcMxuq7yBOAUYGZmfjQijgF+B9wCfAlo35y69eDFxpX6Xsiv1uehPscwoOseyVMjYmFm/jwzZ9X7/ANwMvCH1KG2L+falMy8lHq4f/bs2dssEQ3W8OUfaw0kg/X3UBpsttbflunTp9PZ2cmyZcs29FguW7aMKVOmMGbMmA1lunosu8otW7aMSZMmsXLlSqZOncqYMWNYtmwZ06dP52tf+xrTp0/fsN71s5X6PHknM58HrgLOjIjfByZm5p31e9dn5j82FL8K2GiCTx1O7wX+JzCpnsRzDFXY/CXwG+D/1sXHAJ+KiNuAhcAp9fJF9O7Fxtnpmfkg1f2fH87MuVS9q1/PzLn1+oGZ+fOmY7yW6r7RHtW9oKYbSZK0SYsWLaKzs5PDDjuMW2+9lVtvvZXDDz+czs7ODfdGLlq0iNGjR/PYY49x8MEHc/755zNv3jweffRR2tvb6ezsZO7cucyfP5+ZM2dy2mmnMXPmTBYsWMDcuXNZsGDBhmO1TGZu1ouqZ/E3wE7dvHdbw/Lw+uePG7aNpOotvL1eXwCcXC/f3XSsrwD71MvHAcfUy3OA83up437AeU3brgJuBG6gCoyr6uXvAd9pKrtX17U0nXtEU7kzgYM29zPMTGbNmpXbQtXEg9NgvrY+OXv7VtdAfTTk/61KA8jW/H1dsmRJ7rrrrkk1DyV33XXXXLJkyUZlJkyYsKEMkBMmTMglS5bkkiVLcs8998yIyFGjRiWQo0aNyojIPffcc6NjlQQszz7km16HmyNiFLA/1SScvYFvAE8AV0TEI8Cvgasz8yEaekAzs2uIeHjDthfqY34rIvYFPgV8LCJuAv45IkZm5gtR9UO/nWrIHKpewWg43iZvHsjMH0TEeyPihMz8cr3tyPrcc4GHgV8BO1Ld07m24Xp3Af6el3pc1wMT6+XPRMT9mXlVRCwAJmTmTZv+BCVJkqrZ2r3N2O6tTCtnfPdFr8EyM5+vw9ZSqp7C9fVb10XE66kCYNeQ8Yiu/SJiLHA3Va9g17ag6iF8NdUs8HmZ+auIOIoqRH4NmE8VZO/JzGfrXZ8G1kbEG4ALqYbGe6v3ooiYWZ+3HfgE8F7gHuCkrO4FnQf8MCLuBb5Qn+cHwCmZeXd9qNuBr9ZlVwIX1NtXZOZlvdVDkiRpqNjsxw1t8QnrXslS5TbjvB8E7srMVU3bR1AF2WWZ+WxEjGjswdxafNzQlhvM19YnzgofMIb8v1VpAPH3tXtFZ4WX1NewWDJU1se7oYfta6nuG21clyRJ0mZqyfd1S5IkafAxWEqSJKkIg6UkSZKKMFgOct6ALElS3/l3c8sYLCVJklSEwVKSJElFGCwlSZJUhMFSkiRJRRgsJUmSVITBUpIkSUUYLCVJklSEwVKSJElFDG91BaQtERGtrkLL5NnbD+nrH0jGjx/f6ipI0jZhsNSA5bcjQJ7T6hpIkvQSh8IlSZJUhMFSkiRJRRgsJUmSVITBUpIkSUUYLCVJklSEwVKSJElFGCwlSZJUhMFSkiRJRRgsJUmSVITBUpIkSUUYLCVJklSEwVKSJElFGCwlSZJUhMFSkiRJRRgsJUmSVITBUpIkSUUYLCVJklSEwVKSJElFGCwlSZJUhMFSkiRJRRgsJUmSVITBUpIkSUUYLCVJklSEwVKSJElFGCwlSZJUhMFSkiRJRRgsJUmSVITBUpIkSUUYLCVJklSEwVKSJElFGCwlSZJUhMFSkiRJRRgsJUmSVITBUpIkSUUYLCVJklSEwVKSJElFGCwlSZJUhMFSkiRJRRgsJUmSVITBUpIkSUUYLCVJklSEwVKSJElFGCwlSZJUhMFSkiRJRRgsJUmSVITBUpIkSUUYLCVJklSEwVKSJElFGCwlSZJUhMFSkiRJRRgsJUmSVITBUpIkSUUYLCVJklSEwVKSJElFGCwlSZJUhMFSkiRJRRgsJUmSVITBUpIkSUUYLCVJklSEwVKSJElFGCwlSZJUhMFSkiRJRRgsJUmSVITBUpIkSUUYLCVJklSEwVKSJElFGCwlSZJUhMFSkiRJRRgsJUmSVITBUpIkSUUYLCVJklSEwVKSJElFGCwlSZJUhMFSkiRJRRgsJUmSVITBUpIkSUUYLCVJklSEwVKSJElFGCwlSZJUhMFSkiRJRRgsJUmSVITBUpIkSUUYLCVJklSEwVKSJElFGCwlSZJUhMFSkiRJRRgsJUmSVITBUpIkSUUYLCVJklSEwVKSJElFGCwlSZJUhMFSkiRJRRgsJUmSVITBUpIkSUUYLCVJklSEwVKSJElFGCwlSZJUhMFSkiRJRRgsJUmSVITBUpIkSUUYLCVJklSEwVKSJElFGCwlSZJUhMFSkiRJRRgsJUmSVITBUpIkSUUYLCVJklSEwVKSJElFGCwlSZJUhMFSkiRJRRgsJUmSVITBUpIkSUUYLCVJklSEwVKSJElFRGa2ug5DUkQ8Djxc8JATgScKHk9l2T79l23Tf9k2/Zdt039trbaZmpk79VbIYDlIRMTyzJzd6nqoe7ZP/2Xb9F+2Tf9l2/RfrW4bh8IlSZJUhMFSkiRJRRgsB49LW10BbZLt03/ZNv2XbdN/2Tb9V0vbxnssJUmSVIQ9lpIkSSrCYClJkqQiDJaDQERcFhE/iogzW12XoSoidoiImyLiloj4bkSM7K5dbKvWiYidI+Kf6mXbpp+JiEsi4kP1su3TD0TE+Ii4MSKWR8TX6222TYvV/5fdWS+PiIjrI+KHETF/c7ZtLQbLAS4i/gRoy8x3ALtHxB6trtMQdTjw+cx8L7ASOISmdrGtWu5CYHR37WDbtFZEvAt4dWZeb/v0K0cCf18/E3FsRJyKbdNSETEeuBIYU286EViRmfsA8yJi7GZs2yoMlgPfHOCb9fItwL6tq8rQlZmXZOat9epOwBFs3C5zutmmbSAi3gN0UoX+Odg2/UZEjAD+GngoIv4Y26c/eRKYERHjgMnAbtg2rbYO+O/A0/X6HF76/O8AZm/Gtq3CYDnwjQEeqZdXATu3sC5DXkS8AxgP/Acbt4tt1QIRMRL4c+D0elN37WDbtM5RwP3A54DfBz6J7dNfLAOmAicBvwBGYtu0VGY+nZlPNWzq6/9n26ydDJYD3++A0fXydtimLRMRE4CLgfl03y62VWucDlySmWvqddumf/k94NLMXAn8HVVviu3TP5wNHJeZnwF+CRyGbdPf9PX/s23WTv4DGPhW8NLQw97AQ62rytBV94pdA5yRmQ/TfbvYVq1xAPDJiLgdmAl8CNumP/lXYPd6eTYwDdunvxgP7BURbcDbgPOxbfqbvv6t2WbtNHxrHVjbzLXAnRGxC3AQ8PYW12eoWgC8FVgUEYuAy4Ejm9olsa22ucx8d9dyHS7/iI3bwbZpncuAxRFxCDCC6l6w62yffuE8qv/LpgI/Ar6Avzv9zZXAjfUEuDcDP6Ea8u7Ltq3Cb94ZBOpZYn8I3FEPJ6kf6K5dbKv+wbbp32yf/su26X/qUL8vcHPX/Zd93bZV6mOwlCRJUgneYylJkqQiDJaSJEkqwmApSZKkIgyWkiRJKsJgKUmSpCL+P44TBrszp3rCAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "plt.rcParams['font.sans-serif'] = ['SimHei'] \n",
    "plt.figure(figsize=(10,5))\n",
    "plt.boxplot(\n",
    "    data_supermarket['支付费用（美元）'], # 数据\n",
    "    labels=['支付费用（美元）'], # 数据标签\n",
    "    vert=False, # 横向展示图形\n",
    ")\n",
    "plt.title('支付费用箱线图',fontsize=16)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 案例2：查看数据表中所有数字型数据的分布情况"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['商品单价（美元）', '购买数量（件）', '支付费用（美元）', '收益（美元）', '购物体验评分'], dtype='object')"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 筛选表格中的数字型变量 \n",
    "data_supermarket.describe().columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[ 61.41  ,   7.    , 429.87  ,  21.4935,   9.8   ],\n",
       "       [ 28.45  ,   5.    , 142.25  ,   7.1125,   9.1   ],\n",
       "       [ 12.1   ,   8.    ,  96.8   ,   4.84  ,   8.6   ],\n",
       "       ...,\n",
       "       [ 62.13  ,   6.    , 372.78  ,  18.639 ,   7.4   ],\n",
       "       [ 27.04  ,   4.    , 108.16  ,   5.408 ,   6.9   ],\n",
       "       [ 92.13  ,   6.    , 552.78  , 127.639 ,   8.3   ]])"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_supermarket[data_supermarket.describe().columns].values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "plt.rcParams['font.sans-serif'] = ['SimHei'] \n",
    "plt.figure(figsize=(10,5))\n",
    "plt.boxplot(\n",
    "    data_supermarket[data_supermarket.describe().columns].values, # 数字型变量\n",
    "    labels = data_supermarket.describe().columns, # 变量名称\n",
    "    vert=False, # 横向展示图形\n",
    ")\n",
    "plt.title('超市销售数据表各变量箱线图',fontsize=16)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2.5"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import numpy as np\n",
    "pd.Series([1,2,3,4,None]).median()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
